About

Doug Bowman is a professor in the Department of Computer Science at Virginia Tech. His research interests include virtual reality, augmented reality, 3D user interfaces, human-computer interaction, and virtual environments. He holds a Ph.D. in computer science from Georgia Institute of Technology, obtained in 1999, and also earned a master's degree in computer science from Georgia Tech in 1997. His undergraduate degree is a B.S. in mathematics and computer science from Emory University, completed in 1994. Bowman is involved in advancing the understanding and development of immersive technologies and user interfaces, contributing to the fields of virtual and augmented reality.

Research topics

• Computer Science
• Human–computer interaction
• Engineering
• Multimedia
• Knowledge management
• Telecommunications
• Operating system
• Simulation
• Computer vision

Selected publications

• From Slides to Space: Interactive Scale Navigation for XR Presentations

  2026-03-21

  articleSenior author
  PublisherDOI

• Re-Evaluating Virtual Reality Manipulation Techniques for Precise Alignment of Complex 3D Objects

  IEEE Transactions on Visualization and Computer Graphics · 2026-04-01

  articleSenior author

  Prior research has developed a number of manipulation techniques that can achieve precise object placement in virtual reality, but studies of these techniques typically use simple objects. We conducted a study comparing two existing techniques, (AMP-IT and WISDOM), during alignment of objects with complex geometry to evaluate the potential influence of geometric complexity on performance, usability, workload and preference. Our findings indicate that participants had faster completion times and higher trial completion rates with AMP-IT on high-precision alignment tasks, contrary to earlier findings that used simple objects. Yet WISDOM is still preferred and considered more usable, despite increased workload and poorer performance, exposing participants' willingness to trade objective performance for comfort during use.

  PublisherDOI

• Evaluating the Viability of Additive Models to Predict Task Completion Time for 3D Interactions in Augmented Reality

  Open MIND · 2026-01-30

  preprintSenior author

  Additive models of interaction performance, such as the Keystroke-Level Model (KLM), are tools that allow designers to compare and optimize the performance of user interfaces by summing the predicted times for the atomic components of a specific interaction to predict the total time it would take to complete that interaction. There has been extensive work in creating such additive models for 2D interfaces, but this approach has rarely been explored for 3D user interfaces. We propose a KLM-style additive model, based on existing atomic task models in the literature, to predict task completion time for 3D interaction tasks. We performed two studies to evaluate the feasibility of this approach across multiple input modalities, with one study using a simple menu selection task and the other a more complex manipulation task. We found that several of the models from the literature predicted actual task performance with less than 20% error in both the menu selection and manipulation study. Overall, we found that additive models can predict both absolute and relative performance of input modalities with reasonable accuracy.

  DOI

• Evaluating the Viability of Additive Models to Predict Task Completion Time for 3D Interactions in Augmented Reality

  arXiv (Cornell University) · 2026-01-30

  articleOpen accessSenior author

  Additive models of interaction performance, such as the Keystroke-Level Model (KLM), are tools that allow designers to compare and optimize the performance of user interfaces by summing the predicted times for the atomic components of a specific interaction to predict the total time it would take to complete that interaction. There has been extensive work in creating such additive models for 2D interfaces, but this approach has rarely been explored for 3D user interfaces. We propose a KLM-style additive model, based on existing atomic task models in the literature, to predict task completion time for 3D interaction tasks. We performed two studies to evaluate the feasibility of this approach across multiple input modalities, with one study using a simple menu selection task and the other a more complex manipulation task. We found that several of the models from the literature predicted actual task performance with less than 20% error in both the menu selection and manipulation study. Overall, we found that additive models can predict both absolute and relative performance of input modalities with reasonable accuracy.

  PublisherOA PDF

• Human-AI Interaction in IXR: Design Considerations from Experts

  2026-04-13

  articleOpen accessSenior author

  The integration of artificial intelligence (AI) into extended reality (XR) systems enables new forms of intelligent adaptation. However, to enhance user interaction in XR, human-centered design decision-making is required. Despite increasing interest in intelligent XR (IXR), there is limited expert-driven understanding of how XR designers conceptualize useful intelligent adaptation across different task domains. This paper presents an exploratory qualitative study of XR experts’ design considerations for IXR systems. Data was collected through a roundtable session at iXR Workshop (1st Workshop on Intelligent XR: Harnessing AI for Next-Generation XR User Experiences (iXR)) using a structured open-ended questionnaire and moderated group discussions. Fifteen XR experts developed and reflected on three scenario-based use cases representing industrial operation, social communication, and creative ideation. Our analysis synthesizes XR experts’ perspectives across IXR feature levels and task domains to support early-stage, domain-specific IXR system design.

  PublisherDOI

• When Hands Meet Physics in Virtual Reality: Effects of Interaction Fidelity on User Experience

  2026-04-13 · 1 citations

  articleOpen access

  Physics governs everyday interaction, yet in Virtual Reality (VR) the fidelity of such interactions can diverge from reality. We investigate how Physical Fidelity (virtual object behavior) and Action Fidelity (virtual hand behavior) of physics-driven interaction shape user experience. In a within-subject study (n = 34), participants performed gamified tasks under three conditions: No-Physics (lower Physical and Action Fidelity), Object-Physics (higher Physical, lower Action Fidelity), and Full-Physics (higher Physical and Action Fidelity). Results show that higher Physical Fidelity reduces task efficiency and increases overall workload, with the No-Physics condition outperforming the others in these metrics. When combined with higher Action Fidelity, although efficiency gets even worse in some cases, the Full-Physics condition enhances body ownership and interaction quality. The hybrid Object-Physics condition consistently ranks lowest across all qualitative measures. Interpreting these results through the Interaction Fidelity Model, we offer design implications for VR applications.

  PublisherDOI

• Investigating the Influence of Playback Interactivity during Guided Tours for Asynchronous Collaboration in Virtual Reality

  2025-03-08 · 7 citations

  articleSenior author

  Collaborative virtual environments allow workers to contribute to team projects across space and time. While much research has closely examined the problem of working in different spaces at the same time, few have investigated the best practices for collaborating in those spaces at different times aside from textual and auditory annotations. We designed a system that allows experts to record a tour inside a virtual inspection space, preserving knowledge and providing later observers with insights through a 3D playback of the expert’s inspection. We also created several interactions to ensure that observers are tracking the tour and remaining engaged. We conducted a user study to evaluate the influence of these interactions on an observing user’s information recall and user experience. Findings indicate that independent viewpoint control during a tour enhances the user experience compared to fully passive playback and that additional interactivity can improve auditory and spatial recall of key information conveyed during the tour.

  PublisherDOI

• Towards Intelligent Augmented Reality (iAR): A Taxonomy of Context, an Architecture for iAR, and an Empirical Study

  2025-04-11 · 2 citations

  preprintOpen accessSenior author

  Recent advancements in Augmented Reality (AR) research have highlighted the critical role of context awareness in enhancing interface effectiveness and user experience. This underscores the need for intelligent AR (iAR) interfaces that dynamically adapt across various contexts to provide optimal experiences. In this paper, we (a) propose a comprehensive framework for contextaware inference and adaptation in iAR, (b) introduce a taxonomy that describes context through quantifiable input data, and (c) present an architecture that outlines the implementation of our proposed framework and taxonomy within iAR. Additionally, we present an empirical AR experiment to observe user behavior and record user performance, context, and user-specified adaptations to the AR interfaces within a context-switching scenario. We (d) explore the nuanced relationships between context and user adaptations in this scenario and discuss the significance of our framework in identifying these patterns. This experiment emphasizes the significance of context-awareness in iAR and provides a preliminary training dataset for this specific Scenario.

  PublisherOA PDFDOI

• Planet Purifiers: A Collaborative Immersive Experience Proposing New Modifications to HOMER and Fishing Reel Interaction Techniques

  2025-03-08 · 1 citations

  articleSenior author

  This paper presents our solution to the 2025 3DUI Contest challenge. We aimed to develop a collaborative, immersive experience that raises awareness about trash pollution in natural landscapes while enhancing traditional interaction techniques in virtual environments. To achieve these objectives, we created an engaging multiplayer game where one user collects harmful pollutants while the other user provides medication to impacted wildlife using enhancements to traditional interaction techniques: HOMER and Fishing Reel. We enhanced HOMER to use a cone volume to reduce the precise aiming required by a selection raycast to provide a more efficient means to collect pollutants at large distances, coined as FLOW-MATCH. To improve the animal feed distribution to wildlife far away from the user with Fishing Reel, we created RAWR-XD, an asymmetric bi-manual technique to more conveniently adjust the reeling speed using the non-selecting wrist rotation of the user.

  PublisherDOI

• Exploring Multiscale Navigation of Homogeneous and Dense Objects with Progressive Refinement in Virtual Reality

  2025-03-08 · 2 citations

  articleSenior author

  Locating small features in a large, dense object in virtual reality (VR) poses a significant interaction challenge. While existing multiscale techniques support transitions between various levels of scale, they are not focused on handling dense, homogeneous objects with hidden features. We propose a novel approach that applies the concept of progressive refinement to VR navigation, enabling focused inspections. We conducted a user study where we varied two independent variables in our design, navigation style (STRUCTURED vs. UNSTRUCTURED) and display mode (SELECTION vs. EVERYTHING), to better understand their effects on efficiency and awareness during multiscale navigation. Our results showed that unstructured navigation can be faster than structured and that displaying only the selection can be faster than displaying the entire object. However, using an everything display mode can support better location awareness and object understanding.

  PublisherDOI

Recent grants

• CGV: Small: Collaborative Research: Immersive Visualization and 3D Interaction for Volume Data Analysis

  NSF · $250k · 2013–2017

• EXP: Exploring the potential of mobile augmented reality for scaffolding historical inquiry learning

  NSF · $549k · 2013–2016

• CAREER: Domain-Specific 3D Interaction Techniques for Design and Construction Tasks in Immersive Virtual Environments

  NSF · $500k · 2003–2009

Frequent coauthors

• Lee Lisle

  Virginia Tech

  32 shared

• Chris North

  Virginia Tech

  30 shared

• Feiyu Lu

  JPMorgan Chase & Co (United States)

  28 shared

• Eric D. Ragan

  26 shared

• Leonardo Pavanatto

  Virginia Tech

  24 shared

• Ryan P. McMahan

  University of Central Florida

  24 shared

• Wallace S. Lages

  Universidad del Noreste

  23 shared

• Shakiba Davari

  20 shared

Education

• Ph.D.

  Georgia Institute of Technology

  1999